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Dataset on linear and non-linear indices for discriminating healthy and IUGR fetuses

Authors
  • Signorini, Maria G.1
  • Pini, Nicolò1
  • Malovini, Alberto2
  • Bellazzi, Riccardo3
  • Magenes, Giovanni3
  • 1 Department of Electronics, Information and Bioengineering (DEIB), Politecnico Milano, Piazza Leonardo da Vinci 32, 20133 Milano, Italy
  • 2 IRCCS Fondazione S. Maugeri, Via Maugeri 10, 27100 Pavia, Italy
  • 3 Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Via Ferrata 5, 27100 Pavia, Italy
Type
Published Article
Journal
Data in Brief
Publisher
Elsevier
Publication Date
Jan 29, 2020
Volume
29
Identifiers
DOI: 10.1016/j.dib.2020.105164
PMID: 32071962
PMCID: PMC7015997
Source
PubMed Central
Keywords
Disciplines
  • Medicine and Dentistry
License
Unknown

Abstract

The presented collection of data comprises of a set of 12 linear and nonlinear indices computed at different time scales and extracted from Fetal Heart Rate (FHR) traces acquired through Hewlett Packard CTG fetal monitors (series 1351A), connected to a PC. The sampling frequency of the recorded FHR signal is equal 2 Hz. The recorded populations consist of two groups of fetuses: 60 healthy and 60 Intra Uterine Growth Restricted (IUGR) fetuses. IUGR condition is a fetal condition defined as the abnormal rate of fetal growth. In clinical practice, diagnosis is confirmed at birth and may only be suspected during pregnancy. The pathology is a documented cause of fetal and neonatal morbidity and mortality. The described database was employed in a set of machine learning approaches for the early detection of the IUGR condition: “Integrating machine learning techniques and physiology based heart rate features for antepartum fetal monitoring” [1]. The added value of the proposed indices is their interpretability and close connection to physiological and pathological aspect of FHR regulation. Additional information on data acquisition, feature extraction and potential relevance in clinical practice are discussed in [1].

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